The higher ed admissions data pitch

LEARNING BY DOING—Students who are a best fit for New York Institute of Technology tend to enjoy hands-on problem-solving and can pursue programs such as electrical and computer engineering.

Leveraging Facebook data tools.

College admissions teams now go beyond zip codes and SAT scores to micromatch students who are most likely to apply to, enroll in and succeed at their institutions. In this new era, administrators consider everything from a student’s interests and non-school activities to what they like on Facebook and how long they spent on the institution’s website.

“It’s safe to say college admissions offices have been steeped in this pursuit of better leads and more refined recruitment tactics, and in the use of big data to adapt to changing realities,” says David Hawkins, executive director for educational content and policy at the National Association for College Admission Counseling (NACAC).

Those changes are impacting both marketing overall and the more specific world of students’ college searches.

What’s evolved in the last couple of years is the availability of complex software platforms that can do the tough data analysis work—crunching it down into meaningful, digestible insights. In addition, there’s now “an industry of marketing and communications firms that work hand in glove with colleges to plan and implement their strategies,” says Hawkins.

With technology serving up the exact data models colleges request, recruitment and admissions professionals can embrace a strategy that is similar to how baseball teams analyze player statistics to put together the perfect team.

“It’s about using the data to help shape a freshman class that’s going to graduate,” says Brian G. Williams, vice president for enrollment management and marketing at Roger Williams University in Rhode Island.

Here are some ways data is reshaping admissions and recruitment strategy on campuses today:

3 key considerations for using data responsibly

With big data power comes great data responsibility. After all, students may not even be aware of some of the collection practices taking place. As you delve deeper into data, consider:

1 Privacy

Rule of thumb: Put data to a “reasonability” test, says Mark Hampton, vice president for planning, analytics, and decision support at New York Institute of Technology. “If it allows us to better ensure a student is successful and bringing the right students here, it’s useful data.” The numbers of friends someone has on Facebook, or their relationship status? Not so much.

(cont.)

Pre-season recruitment: Identifying new geographic target areas

Administrators are getting better at determining which data streams can help them make future-facing strategic decisions, says Tristan Denley, chief academic officer and executive vice chancellor of academic affairs for the University System of Georgia.

For example, the system recently introduced a Zillow-like, geocoded interface that lets 28 individual institutions examine the map of Georgia high schools—allowing recruiters to zero in on students who weren’t previously on their radar and plan visits to those schools or perform some other direct outreach.

This tool allows a new, data-informed approach to finding new pockets of students. “It’s natural to target places where you’ve been successful in the past, and it’s hard to look elsewhere because you are just rolling the dice,” says Denley.

In St. Augustine, Florida, Flagler College’s data analytics did the opposite—revealing a potential geographic danger zone. “We found that students from a fairly close geographic area just weren’t retaining well,” says Joseph Provenza, vice president for technology services and chief information officer.

Specifically, students who lived within driving distance of campus (but not super close) were most at risk for dropping out. The reason, Flagler’s administrators surmised, is that those who could go home on a whim were not blending into the campus community, and as a result, were disengaging.

The college is considering a few responses, says Provenza. One is to rethink where recruitment resources are spent. In the meantime, the student life team is looking at strategies for enticing students from this high-risk group to get more involved.

3 key considerations for using data responsibly (cont.)

With big data power comes great data responsibility. After all, students may not even be aware of some of the collection practices taking place. As you delve deeper into data, consider:

2 Ethics

Rule of thumb: Be as transparent as possible. Disclose if you factor demonstrated interest into the admissions decision, and how other information is used, says David Hawkins, executive director for educational content and policy for the National Association for College Admission Counseling.

(cont.)

Application and admissions season: Tracking intent by interactions

Data can take the guesswork out of whether admitted students will choose an institution, says Hawkins of NACAC.

“The more we know about students at the point of application, the better we can predict if they are going to come here or not,” says Mark Hampton, vice president for enrollment and enterprise analytics at New York Institute of Technology.

The university tracks all sorts of interaction with prospective students in its TargetX CRM system, using that data to focus recruitment efforts and build engagement. “The goal is to increase our yield,” says Hampton, who is also interim vice president for enrollment management. “It’s a long game.”

Administrators at Thomas College in Maine, which has approximately 1,000 students, get even more granular, using a custom-built tracking tool that scores each user based on which pages they interact with on the institution’s website.

For example, pulling up the library page might be worth two points because it shows an interest in academics, while pulling up the admissions requirements page might score more points since it indicates the student is thinking about applying.

“Thomas College has a limited amount of admissions counselors, which makes it difficult to reach out to every potential student,” says Peter Levasseur, assistant director of web and digital marketing. “This method aligns the best potential students with our admissions counselors.”

Administrators also have access to a dashboard to see which students have been most active over the last five days, so they know who might be most receptive to a call or other contact.

The challenge is determining how interested a student is in the school before applying, says Daniel McLemore, associate director of marketing communications at Lamar University, part of the Texas State University System. “Before, the application showed intent. But now, the lifecycle must start a lot sooner.”

“It all counts toward a score that says a student is engaged and interested in the things we’re discussing with them, so their likelihood of attending continues to go up every time interaction happens,” says McLemore.

It will take a couple of more lifecycles to put full faith in this scoring system, he says, but early feedback has been positive, and Lamar’s applications and student quality are on the rise.

3 key considerations for using data responsibly (cont.)

With big data power comes great data responsibility. After all, students may not even be aware of some of the collection practices taking place. As you delve deeper into data, consider:

3 Security

Rule of thumb: Ensure data practices pass muster with your network security and legal teams, says Hampton. “Invite the folks who are concerned about the overall well-being of students, their legal rights, and the security of data warehouses into the conversation.”

Post-season insights: Defining success characteristics

Data has helped institutions connect the dots between recruitment, admissions, enrollment management and retention. That’s why many schools are analyzing their current students and recent graduates to figure out which traits are predictors of success. That way, they’ll know which types of students to recruit and admit the next time around.

Naturally, each college may have its own set of success characteristics. At NYIT, for instance, students who show a strong interest in design, problem-solving and using their hands are likely a better fit for the highly technical programs than are those who lean toward liberal arts.

That information can’t easily be gleaned from a GPA or SAT score, says Hampton. “What we’re looking for is that aptitude, that interest—which can be deduced by social media profiles, and from activities in high school and outside of the classroom.”

It’s why someone who identifies as a gamer and who loves science fiction and enters math competitions would likely be a better fit at NYIT than someone who’s an Emily Dickinson buff.

Roger Williams also looks at noncognitive data points to predict which students are destined to succeed, based on what they’ve learned about students who have already performed well.

Having a four-year commitment in activities and working throughout high school, as well as progressing from a member to a leader of an organization over time, are a few important factors, says Williams, vice president for enrollment management.

Like all things digital, the use of data in college recruiting and admissions has only just begun. “We’ve moved from traditional institutional research to business intelligence to data science departments,” says Hampton. “Most universities realize this is how you need to play the game. And if not, you’ll be at a competitive disadvantage.”

Dawn Papandrea, a writer based on Long Island, New York, is a frequent contributor to UB.

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